bxiong commited on
Commit
b79eb3c
·
verified ·
1 Parent(s): 690f3ef

Add files using upload-large-folder tool

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-110/trainer_state.json +198 -0
  2. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/README.md +202 -0
  3. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/adapter_config.json +31 -0
  4. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/trainer_state.json +213 -0
  5. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/README.md +202 -0
  6. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/adapter_config.json +31 -0
  7. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/trainer_state.json +228 -0
  8. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/README.md +202 -0
  9. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/adapter_config.json +31 -0
  10. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/trainer_state.json +243 -0
  11. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/README.md +202 -0
  12. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/adapter_config.json +31 -0
  13. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/trainer_state.json +258 -0
  14. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/README.md +202 -0
  15. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/adapter_config.json +31 -0
  16. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/trainer_state.json +273 -0
  17. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/README.md +202 -0
  18. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/adapter_config.json +31 -0
  19. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/trainer_state.json +288 -0
  20. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/README.md +202 -0
  21. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/adapter_config.json +31 -0
  22. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/trainer_state.json +303 -0
  23. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/README.md +202 -0
  24. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/adapter_config.json +31 -0
  25. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/trainer_state.json +318 -0
  26. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/README.md +202 -0
  27. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/adapter_config.json +31 -0
  28. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/trainer_state.json +333 -0
  29. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/README.md +202 -0
  30. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/adapter_config.json +31 -0
  31. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/trainer_state.json +348 -0
  32. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/README.md +202 -0
  33. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/adapter_config.json +31 -0
  34. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/trainer_state.json +363 -0
  35. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/README.md +202 -0
  36. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/adapter_config.json +31 -0
  37. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/trainer_state.json +378 -0
  38. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/README.md +202 -0
  39. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/adapter_config.json +31 -0
  40. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/trainer_state.json +393 -0
  41. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/README.md +202 -0
  42. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/adapter_config.json +31 -0
  43. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/trainer_state.json +408 -0
  44. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/README.md +202 -0
  45. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/adapter_config.json +31 -0
  46. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/trainer_state.json +423 -0
  47. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/README.md +202 -0
  48. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/adapter_config.json +31 -0
  49. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/trainer_state.json +438 -0
  50. output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/README.md +202 -0
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-110/trainer_state.json ADDED
@@ -0,0 +1,198 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 1.4666666666666668,
5
+ "eval_steps": 10,
6
+ "global_step": 110,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ }
176
+ ],
177
+ "logging_steps": 10,
178
+ "max_steps": 675,
179
+ "num_input_tokens_seen": 0,
180
+ "num_train_epochs": 9,
181
+ "save_steps": 10,
182
+ "stateful_callbacks": {
183
+ "TrainerControl": {
184
+ "args": {
185
+ "should_epoch_stop": false,
186
+ "should_evaluate": false,
187
+ "should_log": false,
188
+ "should_save": true,
189
+ "should_training_stop": false
190
+ },
191
+ "attributes": {}
192
+ }
193
+ },
194
+ "total_flos": 1.80246791847936e+16,
195
+ "train_batch_size": 8,
196
+ "trial_name": null,
197
+ "trial_params": null
198
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-120/trainer_state.json ADDED
@@ -0,0 +1,213 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 1.6,
5
+ "eval_steps": 10,
6
+ "global_step": 120,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ }
191
+ ],
192
+ "logging_steps": 10,
193
+ "max_steps": 675,
194
+ "num_input_tokens_seen": 0,
195
+ "num_train_epochs": 9,
196
+ "save_steps": 10,
197
+ "stateful_callbacks": {
198
+ "TrainerControl": {
199
+ "args": {
200
+ "should_epoch_stop": false,
201
+ "should_evaluate": false,
202
+ "should_log": false,
203
+ "should_save": true,
204
+ "should_training_stop": false
205
+ },
206
+ "attributes": {}
207
+ }
208
+ },
209
+ "total_flos": 1.96632863834112e+16,
210
+ "train_batch_size": 8,
211
+ "trial_name": null,
212
+ "trial_params": null
213
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-130/trainer_state.json ADDED
@@ -0,0 +1,228 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 1.7333333333333334,
5
+ "eval_steps": 10,
6
+ "global_step": 130,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ }
206
+ ],
207
+ "logging_steps": 10,
208
+ "max_steps": 675,
209
+ "num_input_tokens_seen": 0,
210
+ "num_train_epochs": 9,
211
+ "save_steps": 10,
212
+ "stateful_callbacks": {
213
+ "TrainerControl": {
214
+ "args": {
215
+ "should_epoch_stop": false,
216
+ "should_evaluate": false,
217
+ "should_log": false,
218
+ "should_save": true,
219
+ "should_training_stop": false
220
+ },
221
+ "attributes": {}
222
+ }
223
+ },
224
+ "total_flos": 2.13018935820288e+16,
225
+ "train_batch_size": 8,
226
+ "trial_name": null,
227
+ "trial_params": null
228
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-140/trainer_state.json ADDED
@@ -0,0 +1,243 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 1.8666666666666667,
5
+ "eval_steps": 10,
6
+ "global_step": 140,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ }
221
+ ],
222
+ "logging_steps": 10,
223
+ "max_steps": 675,
224
+ "num_input_tokens_seen": 0,
225
+ "num_train_epochs": 9,
226
+ "save_steps": 10,
227
+ "stateful_callbacks": {
228
+ "TrainerControl": {
229
+ "args": {
230
+ "should_epoch_stop": false,
231
+ "should_evaluate": false,
232
+ "should_log": false,
233
+ "should_save": true,
234
+ "should_training_stop": false
235
+ },
236
+ "attributes": {}
237
+ }
238
+ },
239
+ "total_flos": 2.29405007806464e+16,
240
+ "train_batch_size": 8,
241
+ "trial_name": null,
242
+ "trial_params": null
243
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-150/trainer_state.json ADDED
@@ -0,0 +1,258 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.0,
5
+ "eval_steps": 10,
6
+ "global_step": 150,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ }
236
+ ],
237
+ "logging_steps": 10,
238
+ "max_steps": 675,
239
+ "num_input_tokens_seen": 0,
240
+ "num_train_epochs": 9,
241
+ "save_steps": 10,
242
+ "stateful_callbacks": {
243
+ "TrainerControl": {
244
+ "args": {
245
+ "should_epoch_stop": false,
246
+ "should_evaluate": false,
247
+ "should_log": false,
248
+ "should_save": true,
249
+ "should_training_stop": false
250
+ },
251
+ "attributes": {}
252
+ }
253
+ },
254
+ "total_flos": 2.4579107979264e+16,
255
+ "train_batch_size": 8,
256
+ "trial_name": null,
257
+ "trial_params": null
258
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-160/trainer_state.json ADDED
@@ -0,0 +1,273 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.1333333333333333,
5
+ "eval_steps": 10,
6
+ "global_step": 160,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ }
251
+ ],
252
+ "logging_steps": 10,
253
+ "max_steps": 675,
254
+ "num_input_tokens_seen": 0,
255
+ "num_train_epochs": 9,
256
+ "save_steps": 10,
257
+ "stateful_callbacks": {
258
+ "TrainerControl": {
259
+ "args": {
260
+ "should_epoch_stop": false,
261
+ "should_evaluate": false,
262
+ "should_log": false,
263
+ "should_save": true,
264
+ "should_training_stop": false
265
+ },
266
+ "attributes": {}
267
+ }
268
+ },
269
+ "total_flos": 2.62177151778816e+16,
270
+ "train_batch_size": 8,
271
+ "trial_name": null,
272
+ "trial_params": null
273
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-170/trainer_state.json ADDED
@@ -0,0 +1,288 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.2666666666666666,
5
+ "eval_steps": 10,
6
+ "global_step": 170,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ }
266
+ ],
267
+ "logging_steps": 10,
268
+ "max_steps": 675,
269
+ "num_input_tokens_seen": 0,
270
+ "num_train_epochs": 9,
271
+ "save_steps": 10,
272
+ "stateful_callbacks": {
273
+ "TrainerControl": {
274
+ "args": {
275
+ "should_epoch_stop": false,
276
+ "should_evaluate": false,
277
+ "should_log": false,
278
+ "should_save": true,
279
+ "should_training_stop": false
280
+ },
281
+ "attributes": {}
282
+ }
283
+ },
284
+ "total_flos": 2.78563223764992e+16,
285
+ "train_batch_size": 8,
286
+ "trial_name": null,
287
+ "trial_params": null
288
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-180/trainer_state.json ADDED
@@ -0,0 +1,303 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.4,
5
+ "eval_steps": 10,
6
+ "global_step": 180,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ }
281
+ ],
282
+ "logging_steps": 10,
283
+ "max_steps": 675,
284
+ "num_input_tokens_seen": 0,
285
+ "num_train_epochs": 9,
286
+ "save_steps": 10,
287
+ "stateful_callbacks": {
288
+ "TrainerControl": {
289
+ "args": {
290
+ "should_epoch_stop": false,
291
+ "should_evaluate": false,
292
+ "should_log": false,
293
+ "should_save": true,
294
+ "should_training_stop": false
295
+ },
296
+ "attributes": {}
297
+ }
298
+ },
299
+ "total_flos": 2.94949295751168e+16,
300
+ "train_batch_size": 8,
301
+ "trial_name": null,
302
+ "trial_params": null
303
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-190/trainer_state.json ADDED
@@ -0,0 +1,318 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.533333333333333,
5
+ "eval_steps": 10,
6
+ "global_step": 190,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ }
296
+ ],
297
+ "logging_steps": 10,
298
+ "max_steps": 675,
299
+ "num_input_tokens_seen": 0,
300
+ "num_train_epochs": 9,
301
+ "save_steps": 10,
302
+ "stateful_callbacks": {
303
+ "TrainerControl": {
304
+ "args": {
305
+ "should_epoch_stop": false,
306
+ "should_evaluate": false,
307
+ "should_log": false,
308
+ "should_save": true,
309
+ "should_training_stop": false
310
+ },
311
+ "attributes": {}
312
+ }
313
+ },
314
+ "total_flos": 3.11335367737344e+16,
315
+ "train_batch_size": 8,
316
+ "trial_name": null,
317
+ "trial_params": null
318
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-200/trainer_state.json ADDED
@@ -0,0 +1,333 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.6666666666666665,
5
+ "eval_steps": 10,
6
+ "global_step": 200,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ }
311
+ ],
312
+ "logging_steps": 10,
313
+ "max_steps": 675,
314
+ "num_input_tokens_seen": 0,
315
+ "num_train_epochs": 9,
316
+ "save_steps": 10,
317
+ "stateful_callbacks": {
318
+ "TrainerControl": {
319
+ "args": {
320
+ "should_epoch_stop": false,
321
+ "should_evaluate": false,
322
+ "should_log": false,
323
+ "should_save": true,
324
+ "should_training_stop": false
325
+ },
326
+ "attributes": {}
327
+ }
328
+ },
329
+ "total_flos": 3.2772143972352e+16,
330
+ "train_batch_size": 8,
331
+ "trial_name": null,
332
+ "trial_params": null
333
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-210/trainer_state.json ADDED
@@ -0,0 +1,348 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.8,
5
+ "eval_steps": 10,
6
+ "global_step": 210,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.1638202667236328,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 1.5345,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 1.8096415996551514,
321
+ "eval_runtime": 43.8206,
322
+ "eval_samples_per_second": 22.82,
323
+ "eval_steps_per_second": 2.853,
324
+ "step": 210
325
+ }
326
+ ],
327
+ "logging_steps": 10,
328
+ "max_steps": 675,
329
+ "num_input_tokens_seen": 0,
330
+ "num_train_epochs": 9,
331
+ "save_steps": 10,
332
+ "stateful_callbacks": {
333
+ "TrainerControl": {
334
+ "args": {
335
+ "should_epoch_stop": false,
336
+ "should_evaluate": false,
337
+ "should_log": false,
338
+ "should_save": true,
339
+ "should_training_stop": false
340
+ },
341
+ "attributes": {}
342
+ }
343
+ },
344
+ "total_flos": 3.44107511709696e+16,
345
+ "train_batch_size": 8,
346
+ "trial_name": null,
347
+ "trial_params": null
348
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-220/trainer_state.json ADDED
@@ -0,0 +1,363 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 2.9333333333333336,
5
+ "eval_steps": 10,
6
+ "global_step": 220,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.1638202667236328,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 1.5345,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 1.8096415996551514,
321
+ "eval_runtime": 43.8206,
322
+ "eval_samples_per_second": 22.82,
323
+ "eval_steps_per_second": 2.853,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.2765487432479858,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 1.6074,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 1.810752034187317,
336
+ "eval_runtime": 43.8178,
337
+ "eval_samples_per_second": 22.822,
338
+ "eval_steps_per_second": 2.853,
339
+ "step": 220
340
+ }
341
+ ],
342
+ "logging_steps": 10,
343
+ "max_steps": 675,
344
+ "num_input_tokens_seen": 0,
345
+ "num_train_epochs": 9,
346
+ "save_steps": 10,
347
+ "stateful_callbacks": {
348
+ "TrainerControl": {
349
+ "args": {
350
+ "should_epoch_stop": false,
351
+ "should_evaluate": false,
352
+ "should_log": false,
353
+ "should_save": true,
354
+ "should_training_stop": false
355
+ },
356
+ "attributes": {}
357
+ }
358
+ },
359
+ "total_flos": 3.60493583695872e+16,
360
+ "train_batch_size": 8,
361
+ "trial_name": null,
362
+ "trial_params": null
363
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-230/trainer_state.json ADDED
@@ -0,0 +1,378 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 3.066666666666667,
5
+ "eval_steps": 10,
6
+ "global_step": 230,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.1638202667236328,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 1.5345,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 1.8096415996551514,
321
+ "eval_runtime": 43.8206,
322
+ "eval_samples_per_second": 22.82,
323
+ "eval_steps_per_second": 2.853,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.2765487432479858,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 1.6074,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 1.810752034187317,
336
+ "eval_runtime": 43.8178,
337
+ "eval_samples_per_second": 22.822,
338
+ "eval_steps_per_second": 2.853,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.4451857805252075,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 1.5139,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 1.8353334665298462,
351
+ "eval_runtime": 43.831,
352
+ "eval_samples_per_second": 22.815,
353
+ "eval_steps_per_second": 2.852,
354
+ "step": 230
355
+ }
356
+ ],
357
+ "logging_steps": 10,
358
+ "max_steps": 675,
359
+ "num_input_tokens_seen": 0,
360
+ "num_train_epochs": 9,
361
+ "save_steps": 10,
362
+ "stateful_callbacks": {
363
+ "TrainerControl": {
364
+ "args": {
365
+ "should_epoch_stop": false,
366
+ "should_evaluate": false,
367
+ "should_log": false,
368
+ "should_save": true,
369
+ "should_training_stop": false
370
+ },
371
+ "attributes": {}
372
+ }
373
+ },
374
+ "total_flos": 3.76879655682048e+16,
375
+ "train_batch_size": 8,
376
+ "trial_name": null,
377
+ "trial_params": null
378
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-240/trainer_state.json ADDED
@@ -0,0 +1,393 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 3.2,
5
+ "eval_steps": 10,
6
+ "global_step": 240,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.1638202667236328,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 1.5345,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 1.8096415996551514,
321
+ "eval_runtime": 43.8206,
322
+ "eval_samples_per_second": 22.82,
323
+ "eval_steps_per_second": 2.853,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.2765487432479858,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 1.6074,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 1.810752034187317,
336
+ "eval_runtime": 43.8178,
337
+ "eval_samples_per_second": 22.822,
338
+ "eval_steps_per_second": 2.853,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.4451857805252075,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 1.5139,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 1.8353334665298462,
351
+ "eval_runtime": 43.831,
352
+ "eval_samples_per_second": 22.815,
353
+ "eval_steps_per_second": 2.852,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 1.697195291519165,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 1.3564,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 1.8831367492675781,
366
+ "eval_runtime": 43.8285,
367
+ "eval_samples_per_second": 22.816,
368
+ "eval_steps_per_second": 2.852,
369
+ "step": 240
370
+ }
371
+ ],
372
+ "logging_steps": 10,
373
+ "max_steps": 675,
374
+ "num_input_tokens_seen": 0,
375
+ "num_train_epochs": 9,
376
+ "save_steps": 10,
377
+ "stateful_callbacks": {
378
+ "TrainerControl": {
379
+ "args": {
380
+ "should_epoch_stop": false,
381
+ "should_evaluate": false,
382
+ "should_log": false,
383
+ "should_save": true,
384
+ "should_training_stop": false
385
+ },
386
+ "attributes": {}
387
+ }
388
+ },
389
+ "total_flos": 3.93265727668224e+16,
390
+ "train_batch_size": 8,
391
+ "trial_name": null,
392
+ "trial_params": null
393
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-250/trainer_state.json ADDED
@@ -0,0 +1,408 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 3.3333333333333335,
5
+ "eval_steps": 10,
6
+ "global_step": 250,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.1638202667236328,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 1.5345,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 1.8096415996551514,
321
+ "eval_runtime": 43.8206,
322
+ "eval_samples_per_second": 22.82,
323
+ "eval_steps_per_second": 2.853,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.2765487432479858,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 1.6074,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 1.810752034187317,
336
+ "eval_runtime": 43.8178,
337
+ "eval_samples_per_second": 22.822,
338
+ "eval_steps_per_second": 2.853,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.4451857805252075,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 1.5139,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 1.8353334665298462,
351
+ "eval_runtime": 43.831,
352
+ "eval_samples_per_second": 22.815,
353
+ "eval_steps_per_second": 2.852,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 1.697195291519165,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 1.3564,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 1.8831367492675781,
366
+ "eval_runtime": 43.8285,
367
+ "eval_samples_per_second": 22.816,
368
+ "eval_steps_per_second": 2.852,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 1.650194525718689,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 1.3952,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 1.8923019170761108,
381
+ "eval_runtime": 43.8237,
382
+ "eval_samples_per_second": 22.819,
383
+ "eval_steps_per_second": 2.852,
384
+ "step": 250
385
+ }
386
+ ],
387
+ "logging_steps": 10,
388
+ "max_steps": 675,
389
+ "num_input_tokens_seen": 0,
390
+ "num_train_epochs": 9,
391
+ "save_steps": 10,
392
+ "stateful_callbacks": {
393
+ "TrainerControl": {
394
+ "args": {
395
+ "should_epoch_stop": false,
396
+ "should_evaluate": false,
397
+ "should_log": false,
398
+ "should_save": true,
399
+ "should_training_stop": false
400
+ },
401
+ "attributes": {}
402
+ }
403
+ },
404
+ "total_flos": 4.096517996544e+16,
405
+ "train_batch_size": 8,
406
+ "trial_name": null,
407
+ "trial_params": null
408
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-260/trainer_state.json ADDED
@@ -0,0 +1,423 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 3.466666666666667,
5
+ "eval_steps": 10,
6
+ "global_step": 260,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.1638202667236328,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 1.5345,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 1.8096415996551514,
321
+ "eval_runtime": 43.8206,
322
+ "eval_samples_per_second": 22.82,
323
+ "eval_steps_per_second": 2.853,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.2765487432479858,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 1.6074,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 1.810752034187317,
336
+ "eval_runtime": 43.8178,
337
+ "eval_samples_per_second": 22.822,
338
+ "eval_steps_per_second": 2.853,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.4451857805252075,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 1.5139,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 1.8353334665298462,
351
+ "eval_runtime": 43.831,
352
+ "eval_samples_per_second": 22.815,
353
+ "eval_steps_per_second": 2.852,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 1.697195291519165,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 1.3564,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 1.8831367492675781,
366
+ "eval_runtime": 43.8285,
367
+ "eval_samples_per_second": 22.816,
368
+ "eval_steps_per_second": 2.852,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 1.650194525718689,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 1.3952,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 1.8923019170761108,
381
+ "eval_runtime": 43.8237,
382
+ "eval_samples_per_second": 22.819,
383
+ "eval_steps_per_second": 2.852,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 1.7771501541137695,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 1.2664,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 1.8947919607162476,
396
+ "eval_runtime": 43.851,
397
+ "eval_samples_per_second": 22.804,
398
+ "eval_steps_per_second": 2.851,
399
+ "step": 260
400
+ }
401
+ ],
402
+ "logging_steps": 10,
403
+ "max_steps": 675,
404
+ "num_input_tokens_seen": 0,
405
+ "num_train_epochs": 9,
406
+ "save_steps": 10,
407
+ "stateful_callbacks": {
408
+ "TrainerControl": {
409
+ "args": {
410
+ "should_epoch_stop": false,
411
+ "should_evaluate": false,
412
+ "should_log": false,
413
+ "should_save": true,
414
+ "should_training_stop": false
415
+ },
416
+ "attributes": {}
417
+ }
418
+ },
419
+ "total_flos": 4.26037871640576e+16,
420
+ "train_batch_size": 8,
421
+ "trial_name": null,
422
+ "trial_params": null
423
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/adapter_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "/workspace/pythia-6_9b",
5
+ "bias": "none",
6
+ "fan_in_fan_out": false,
7
+ "inference_mode": true,
8
+ "init_lora_weights": true,
9
+ "layer_replication": null,
10
+ "layers_pattern": null,
11
+ "layers_to_transform": null,
12
+ "loftq_config": {},
13
+ "lora_alpha": 32,
14
+ "lora_dropout": 0.1,
15
+ "megatron_config": null,
16
+ "megatron_core": "megatron.core",
17
+ "modules_to_save": null,
18
+ "peft_type": "LORA",
19
+ "r": 8,
20
+ "rank_pattern": {},
21
+ "revision": null,
22
+ "target_modules": [
23
+ "dense",
24
+ "dense_4h_to_h",
25
+ "query_key_value",
26
+ "dense_h_to_4h"
27
+ ],
28
+ "task_type": "CAUSAL_LM",
29
+ "use_dora": false,
30
+ "use_rslora": false
31
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-270/trainer_state.json ADDED
@@ -0,0 +1,438 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": 1.7508132457733154,
3
+ "best_model_checkpoint": "./output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-80",
4
+ "epoch": 3.6,
5
+ "eval_steps": 10,
6
+ "global_step": 270,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13333333333333333,
13
+ "grad_norm": 0.3951323926448822,
14
+ "learning_rate": 7.881481481481482e-05,
15
+ "loss": 1.8421,
16
+ "step": 10
17
+ },
18
+ {
19
+ "epoch": 0.13333333333333333,
20
+ "eval_loss": 1.7700647115707397,
21
+ "eval_runtime": 43.86,
22
+ "eval_samples_per_second": 22.8,
23
+ "eval_steps_per_second": 2.85,
24
+ "step": 10
25
+ },
26
+ {
27
+ "epoch": 0.26666666666666666,
28
+ "grad_norm": 0.3800930380821228,
29
+ "learning_rate": 7.762962962962963e-05,
30
+ "loss": 1.7715,
31
+ "step": 20
32
+ },
33
+ {
34
+ "epoch": 0.26666666666666666,
35
+ "eval_loss": 1.7666271924972534,
36
+ "eval_runtime": 43.8435,
37
+ "eval_samples_per_second": 22.808,
38
+ "eval_steps_per_second": 2.851,
39
+ "step": 20
40
+ },
41
+ {
42
+ "epoch": 0.4,
43
+ "grad_norm": 0.3974359333515167,
44
+ "learning_rate": 7.644444444444445e-05,
45
+ "loss": 1.7799,
46
+ "step": 30
47
+ },
48
+ {
49
+ "epoch": 0.4,
50
+ "eval_loss": 1.7623893022537231,
51
+ "eval_runtime": 43.863,
52
+ "eval_samples_per_second": 22.798,
53
+ "eval_steps_per_second": 2.85,
54
+ "step": 30
55
+ },
56
+ {
57
+ "epoch": 0.5333333333333333,
58
+ "grad_norm": 0.37877357006073,
59
+ "learning_rate": 7.525925925925926e-05,
60
+ "loss": 1.7416,
61
+ "step": 40
62
+ },
63
+ {
64
+ "epoch": 0.5333333333333333,
65
+ "eval_loss": 1.7585530281066895,
66
+ "eval_runtime": 43.8506,
67
+ "eval_samples_per_second": 22.805,
68
+ "eval_steps_per_second": 2.851,
69
+ "step": 40
70
+ },
71
+ {
72
+ "epoch": 0.6666666666666666,
73
+ "grad_norm": 0.3691335618495941,
74
+ "learning_rate": 7.407407407407409e-05,
75
+ "loss": 1.754,
76
+ "step": 50
77
+ },
78
+ {
79
+ "epoch": 0.6666666666666666,
80
+ "eval_loss": 1.7555732727050781,
81
+ "eval_runtime": 43.8591,
82
+ "eval_samples_per_second": 22.8,
83
+ "eval_steps_per_second": 2.85,
84
+ "step": 50
85
+ },
86
+ {
87
+ "epoch": 0.8,
88
+ "grad_norm": 0.3394964337348938,
89
+ "learning_rate": 7.28888888888889e-05,
90
+ "loss": 1.639,
91
+ "step": 60
92
+ },
93
+ {
94
+ "epoch": 0.8,
95
+ "eval_loss": 1.7534734010696411,
96
+ "eval_runtime": 43.8608,
97
+ "eval_samples_per_second": 22.799,
98
+ "eval_steps_per_second": 2.85,
99
+ "step": 60
100
+ },
101
+ {
102
+ "epoch": 0.9333333333333333,
103
+ "grad_norm": 0.317234069108963,
104
+ "learning_rate": 7.170370370370371e-05,
105
+ "loss": 1.7729,
106
+ "step": 70
107
+ },
108
+ {
109
+ "epoch": 0.9333333333333333,
110
+ "eval_loss": 1.7515993118286133,
111
+ "eval_runtime": 43.8388,
112
+ "eval_samples_per_second": 22.811,
113
+ "eval_steps_per_second": 2.851,
114
+ "step": 70
115
+ },
116
+ {
117
+ "epoch": 1.0666666666666667,
118
+ "grad_norm": 0.3309251666069031,
119
+ "learning_rate": 7.051851851851853e-05,
120
+ "loss": 1.8009,
121
+ "step": 80
122
+ },
123
+ {
124
+ "epoch": 1.0666666666666667,
125
+ "eval_loss": 1.7508132457733154,
126
+ "eval_runtime": 43.8535,
127
+ "eval_samples_per_second": 22.803,
128
+ "eval_steps_per_second": 2.85,
129
+ "step": 80
130
+ },
131
+ {
132
+ "epoch": 1.2,
133
+ "grad_norm": 0.4126473367214203,
134
+ "learning_rate": 6.933333333333334e-05,
135
+ "loss": 1.6602,
136
+ "step": 90
137
+ },
138
+ {
139
+ "epoch": 1.2,
140
+ "eval_loss": 1.753326177597046,
141
+ "eval_runtime": 43.86,
142
+ "eval_samples_per_second": 22.8,
143
+ "eval_steps_per_second": 2.85,
144
+ "step": 90
145
+ },
146
+ {
147
+ "epoch": 1.3333333333333333,
148
+ "grad_norm": 0.5640483498573303,
149
+ "learning_rate": 6.814814814814815e-05,
150
+ "loss": 1.5879,
151
+ "step": 100
152
+ },
153
+ {
154
+ "epoch": 1.3333333333333333,
155
+ "eval_loss": 1.7581162452697754,
156
+ "eval_runtime": 43.8488,
157
+ "eval_samples_per_second": 22.806,
158
+ "eval_steps_per_second": 2.851,
159
+ "step": 100
160
+ },
161
+ {
162
+ "epoch": 1.4666666666666668,
163
+ "grad_norm": 0.6418269276618958,
164
+ "learning_rate": 6.696296296296296e-05,
165
+ "loss": 1.7067,
166
+ "step": 110
167
+ },
168
+ {
169
+ "epoch": 1.4666666666666668,
170
+ "eval_loss": 1.7590935230255127,
171
+ "eval_runtime": 43.8372,
172
+ "eval_samples_per_second": 22.812,
173
+ "eval_steps_per_second": 2.851,
174
+ "step": 110
175
+ },
176
+ {
177
+ "epoch": 1.6,
178
+ "grad_norm": 0.603199303150177,
179
+ "learning_rate": 6.577777777777777e-05,
180
+ "loss": 1.7311,
181
+ "step": 120
182
+ },
183
+ {
184
+ "epoch": 1.6,
185
+ "eval_loss": 1.760871410369873,
186
+ "eval_runtime": 43.828,
187
+ "eval_samples_per_second": 22.816,
188
+ "eval_steps_per_second": 2.852,
189
+ "step": 120
190
+ },
191
+ {
192
+ "epoch": 1.7333333333333334,
193
+ "grad_norm": 0.7207424640655518,
194
+ "learning_rate": 6.45925925925926e-05,
195
+ "loss": 1.7103,
196
+ "step": 130
197
+ },
198
+ {
199
+ "epoch": 1.7333333333333334,
200
+ "eval_loss": 1.761257529258728,
201
+ "eval_runtime": 43.8422,
202
+ "eval_samples_per_second": 22.809,
203
+ "eval_steps_per_second": 2.851,
204
+ "step": 130
205
+ },
206
+ {
207
+ "epoch": 1.8666666666666667,
208
+ "grad_norm": 0.6793868541717529,
209
+ "learning_rate": 6.340740740740741e-05,
210
+ "loss": 1.6574,
211
+ "step": 140
212
+ },
213
+ {
214
+ "epoch": 1.8666666666666667,
215
+ "eval_loss": 1.7610187530517578,
216
+ "eval_runtime": 43.8261,
217
+ "eval_samples_per_second": 22.817,
218
+ "eval_steps_per_second": 2.852,
219
+ "step": 140
220
+ },
221
+ {
222
+ "epoch": 2.0,
223
+ "grad_norm": 0.7147842049598694,
224
+ "learning_rate": 6.222222222222223e-05,
225
+ "loss": 1.6357,
226
+ "step": 150
227
+ },
228
+ {
229
+ "epoch": 2.0,
230
+ "eval_loss": 1.763314962387085,
231
+ "eval_runtime": 43.8315,
232
+ "eval_samples_per_second": 22.815,
233
+ "eval_steps_per_second": 2.852,
234
+ "step": 150
235
+ },
236
+ {
237
+ "epoch": 2.1333333333333333,
238
+ "grad_norm": 0.8159098625183105,
239
+ "learning_rate": 6.103703703703704e-05,
240
+ "loss": 1.62,
241
+ "step": 160
242
+ },
243
+ {
244
+ "epoch": 2.1333333333333333,
245
+ "eval_loss": 1.7846354246139526,
246
+ "eval_runtime": 43.8212,
247
+ "eval_samples_per_second": 22.82,
248
+ "eval_steps_per_second": 2.853,
249
+ "step": 160
250
+ },
251
+ {
252
+ "epoch": 2.2666666666666666,
253
+ "grad_norm": 1.0052918195724487,
254
+ "learning_rate": 5.9851851851851855e-05,
255
+ "loss": 1.5109,
256
+ "step": 170
257
+ },
258
+ {
259
+ "epoch": 2.2666666666666666,
260
+ "eval_loss": 1.8005082607269287,
261
+ "eval_runtime": 43.8314,
262
+ "eval_samples_per_second": 22.815,
263
+ "eval_steps_per_second": 2.852,
264
+ "step": 170
265
+ },
266
+ {
267
+ "epoch": 2.4,
268
+ "grad_norm": 1.089106559753418,
269
+ "learning_rate": 5.8666666666666665e-05,
270
+ "loss": 1.5658,
271
+ "step": 180
272
+ },
273
+ {
274
+ "epoch": 2.4,
275
+ "eval_loss": 1.8088901042938232,
276
+ "eval_runtime": 43.8245,
277
+ "eval_samples_per_second": 22.818,
278
+ "eval_steps_per_second": 2.852,
279
+ "step": 180
280
+ },
281
+ {
282
+ "epoch": 2.533333333333333,
283
+ "grad_norm": 1.1667160987854004,
284
+ "learning_rate": 5.748148148148149e-05,
285
+ "loss": 1.6316,
286
+ "step": 190
287
+ },
288
+ {
289
+ "epoch": 2.533333333333333,
290
+ "eval_loss": 1.8114306926727295,
291
+ "eval_runtime": 43.8195,
292
+ "eval_samples_per_second": 22.821,
293
+ "eval_steps_per_second": 2.853,
294
+ "step": 190
295
+ },
296
+ {
297
+ "epoch": 2.6666666666666665,
298
+ "grad_norm": 1.215566873550415,
299
+ "learning_rate": 5.62962962962963e-05,
300
+ "loss": 1.4806,
301
+ "step": 200
302
+ },
303
+ {
304
+ "epoch": 2.6666666666666665,
305
+ "eval_loss": 1.811687707901001,
306
+ "eval_runtime": 43.8494,
307
+ "eval_samples_per_second": 22.805,
308
+ "eval_steps_per_second": 2.851,
309
+ "step": 200
310
+ },
311
+ {
312
+ "epoch": 2.8,
313
+ "grad_norm": 1.1638202667236328,
314
+ "learning_rate": 5.511111111111112e-05,
315
+ "loss": 1.5345,
316
+ "step": 210
317
+ },
318
+ {
319
+ "epoch": 2.8,
320
+ "eval_loss": 1.8096415996551514,
321
+ "eval_runtime": 43.8206,
322
+ "eval_samples_per_second": 22.82,
323
+ "eval_steps_per_second": 2.853,
324
+ "step": 210
325
+ },
326
+ {
327
+ "epoch": 2.9333333333333336,
328
+ "grad_norm": 1.2765487432479858,
329
+ "learning_rate": 5.392592592592593e-05,
330
+ "loss": 1.6074,
331
+ "step": 220
332
+ },
333
+ {
334
+ "epoch": 2.9333333333333336,
335
+ "eval_loss": 1.810752034187317,
336
+ "eval_runtime": 43.8178,
337
+ "eval_samples_per_second": 22.822,
338
+ "eval_steps_per_second": 2.853,
339
+ "step": 220
340
+ },
341
+ {
342
+ "epoch": 3.066666666666667,
343
+ "grad_norm": 1.4451857805252075,
344
+ "learning_rate": 5.274074074074074e-05,
345
+ "loss": 1.5139,
346
+ "step": 230
347
+ },
348
+ {
349
+ "epoch": 3.066666666666667,
350
+ "eval_loss": 1.8353334665298462,
351
+ "eval_runtime": 43.831,
352
+ "eval_samples_per_second": 22.815,
353
+ "eval_steps_per_second": 2.852,
354
+ "step": 230
355
+ },
356
+ {
357
+ "epoch": 3.2,
358
+ "grad_norm": 1.697195291519165,
359
+ "learning_rate": 5.155555555555556e-05,
360
+ "loss": 1.3564,
361
+ "step": 240
362
+ },
363
+ {
364
+ "epoch": 3.2,
365
+ "eval_loss": 1.8831367492675781,
366
+ "eval_runtime": 43.8285,
367
+ "eval_samples_per_second": 22.816,
368
+ "eval_steps_per_second": 2.852,
369
+ "step": 240
370
+ },
371
+ {
372
+ "epoch": 3.3333333333333335,
373
+ "grad_norm": 1.650194525718689,
374
+ "learning_rate": 5.037037037037037e-05,
375
+ "loss": 1.3952,
376
+ "step": 250
377
+ },
378
+ {
379
+ "epoch": 3.3333333333333335,
380
+ "eval_loss": 1.8923019170761108,
381
+ "eval_runtime": 43.8237,
382
+ "eval_samples_per_second": 22.819,
383
+ "eval_steps_per_second": 2.852,
384
+ "step": 250
385
+ },
386
+ {
387
+ "epoch": 3.466666666666667,
388
+ "grad_norm": 1.7771501541137695,
389
+ "learning_rate": 4.918518518518519e-05,
390
+ "loss": 1.2664,
391
+ "step": 260
392
+ },
393
+ {
394
+ "epoch": 3.466666666666667,
395
+ "eval_loss": 1.8947919607162476,
396
+ "eval_runtime": 43.851,
397
+ "eval_samples_per_second": 22.804,
398
+ "eval_steps_per_second": 2.851,
399
+ "step": 260
400
+ },
401
+ {
402
+ "epoch": 3.6,
403
+ "grad_norm": 1.5858917236328125,
404
+ "learning_rate": 4.8e-05,
405
+ "loss": 1.4785,
406
+ "step": 270
407
+ },
408
+ {
409
+ "epoch": 3.6,
410
+ "eval_loss": 1.8847408294677734,
411
+ "eval_runtime": 43.8427,
412
+ "eval_samples_per_second": 22.809,
413
+ "eval_steps_per_second": 2.851,
414
+ "step": 270
415
+ }
416
+ ],
417
+ "logging_steps": 10,
418
+ "max_steps": 675,
419
+ "num_input_tokens_seen": 0,
420
+ "num_train_epochs": 9,
421
+ "save_steps": 10,
422
+ "stateful_callbacks": {
423
+ "TrainerControl": {
424
+ "args": {
425
+ "should_epoch_stop": false,
426
+ "should_evaluate": false,
427
+ "should_log": false,
428
+ "should_save": true,
429
+ "should_training_stop": false
430
+ },
431
+ "attributes": {}
432
+ }
433
+ },
434
+ "total_flos": 4.42423943626752e+16,
435
+ "train_batch_size": 8,
436
+ "trial_name": null,
437
+ "trial_params": null
438
+ }
output_ft_more_layers_freelaw_epoch_9_mlp/pythia-6_9b-member-6_9b-epoch-9-pile-full-600-subsets-freelaw-8e-05/checkpoint-280/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: /workspace/pythia-6_9b
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.13.2